Meaningful Secret Image Sharing with Saliency Detection

Secret image sharing (SIS), as one of the applications of information theory in information security protection, has been widely used in many areas, such as blockchain, identity authentication and distributed cloud storage. In traditional secret image sharing schemes, noise-like shadows introduce difficulties into shadow management and increase the risk of attacks. Meaningful secret image sharing is thus proposed to solve these problems. Previous meaningful SIS schemes have employed steganography to hide shares into cover images, and their covers are always binary images. These schemes usually include pixel expansion and low visual quality shadows. To improve the shadow quality, we design a meaningful secret image sharing scheme with saliency detection. Saliency detection is used to determine the salient regions of cover images. In our proposed scheme, we improve the quality of salient regions that are sensitive to the human vision system. In this way, we obtain meaningful shadows with better visual quality. Experiment results and comparisons demonstrate the effectiveness of our proposed scheme.     

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我国文献资源整体化建设的障碍及对策

分析了我国文献资源整体化建设的现状，探讨了我国文献资源整体化建设的障碍和存在问题，针对这些问题提出了相应的对策。     

高师院校图书馆为本地区基础教育服务的途径探讨

鉴于高师院校图书馆具有的资源优势，探讨了为本地区基础教育服务的必要性和可行性，提出了以阅读、开放、科教指导、讲座等具体服务基础教育的形式和途径。     

Dynamic Niching Genetic Algorithm with Data Attraction for Automatic Clustering

A genetic clustering algorithm was developed based on dynamic niching with data attraction. The algorithm uses the concept of Coulomb attraction to model the attraction between data points. Then, the niches with data attraction are dynamically identified in each generation to automatically evolve the optimal number of clusters as well as the cluster centers of the data set without using cluster validity functions or a variance-covariance matrix. Therefore, this clustering scheme does not need to pre-specify the number of clusters as in existing methods. Several data sets with widely varying characteristics are used to demonstrate the superiority of this algorithm. Experimental results show that the performance of this clustering algorithm is high, effective, and flexible.     

区域医学信息资源共享策略研究

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